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A First-Generation Multiplex Biomarker Analysis of Urine for the Early Detection of Prostate Cancer

405

Citations

29

References

2008

Year

TLDR

Prostate‑specific antigen testing lacks specificity, prompting interest in urinary biomarkers such as the noncoding RNA PCA3 to improve prostate cancer detection. The study quantified seven candidate urinary biomarkers, including PCA3, by quantitative PCR on sedimented urine from 234 patients scheduled for biopsy or prostatectomy. A multiplex panel comprising GOLPH2, SPINK1, PCA3, and TMPRSS2:ERG achieved an AUC of 0.758, outperforming PSA or PCA3 alone (AUC 0.662) with 65.9% sensitivity, 76.0% specificity, and provided a framework for optimized urine tests. Published in Cancer Research 2008, vol.

Abstract

Abstract Although prostate-specific antigen (PSA) serum level is currently the standard of care for prostate cancer screening in the United States, it lacks ideal specificity and additional biomarkers are needed to supplement or potentially replace serum PSA testing. Emerging evidence suggests that monitoring the noncoding RNA transcript PCA3 in urine may be useful in detecting prostate cancer in patients with elevated PSA levels. Here, we show that a multiplex panel of urine transcripts outperforms PCA3 transcript alone for the detection of prostate cancer. We measured the expression of seven putative prostate cancer biomarkers, including PCA3, in sedimented urine using quantitative PCR on a cohort of 234 patients presenting for biopsy or radical prostatectomy. By univariate analysis, we found that increased GOLPH2, SPINK1, and PCA3 transcript expression and TMPRSS2:ERG fusion status were significant predictors of prostate cancer. Multivariate regression analysis showed that a multiplexed model, including these biomarkers, outperformed serum PSA or PCA3 alone in detecting prostate cancer. The area under the receiver-operating characteristic curve was 0.758 for the multiplexed model versus 0.662 for PCA3 alone (P = 0.003). The sensitivity and specificity for the multiplexed model were 65.9% and 76.0%, respectively, and the positive and negative predictive values were 79.8% and 60.8%, respectively. Taken together, these results provide the framework for the development of highly optimized, multiplex urine biomarker tests for more accurate detection of prostate cancer. [Cancer Res 2008;68(3):645–9]

References

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